用最小的事件信号进行连续的上市后顺序安全监控。

Pub Date : 2017-07-01
Martin Kulldorff, Ivair R Silva
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引用次数: 0

摘要

疾病预防控制中心疫苗安全数据链项目率先使用接近实时的上市后疫苗安全监测来快速发现不良事件。每周进行分析,使用连续顺序方法,使研究人员能够在保持正确的整体alpha水平的同时,近乎连续地评估数据。通过连续的连续监测,在观察到一两个不良事件后,零假设可能被拒绝。在本文中,我们探索连续顺序监控,当我们不允许null被拒绝,直到最小数量的观察事件已经发生。我们还评估了延迟开始的连续序列分析,直到达到一定的样本量。提供了具有精确临界值、统计功率和平均信号时间的表。我们表明,使用第一种选择,在保持α电平不变的情况下,既可以增加功率又可以减少信号的预期时间。第二种选择只有在由于后勤原因而推迟开始监测的情况下才有用,即在第一次分析时有一组数据可用,随后进行连续或接近连续的监测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Continuous Post-Market Sequential Safety Surveillance with Minimum Events to Signal.

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Continuous Post-Market Sequential Safety Surveillance with Minimum Events to Signal.

The CDC Vaccine Safety Datalink project has pioneered the use of near real-time post-market vaccine safety surveillance for the rapid detection of adverse events. Doing weekly analyses, continuous sequential methods are used, allowing investigators to evaluate the data near-continuously while still maintaining the correct overall alpha level. With continuous sequential monitoring, the null hypothesis may be rejected after only one or two adverse events are observed. In this paper, we explore continuous sequential monitoring when we do not allow the null to be rejected until a minimum number of observed events have occurred. We also evaluate continuous sequential analysis with a delayed start until a certain sample size has been attained. Tables with exact critical values, statistical power and the average times to signal are provided. We show that, with the first option, it is possible to both increase the power and reduce the expected time to signal, while keeping the alpha level the same. The second option is only useful if the start of the surveillance is delayed for logistical reasons, when there is a group of data available at the first analysis, followed by continuous or near-continuous monitoring thereafter.

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